{"id":{"repo_id":"uthm","oai_identifier":"oai:eprints.uthm.edu.my:629"},"canonical_url":"https://search.dev.ndltd.org/etd/uthm/oai:eprints.uthm.edu.my:629","repository":{"repo_id":"uthm","name":"Universiti Tun Hussein Onn Malaysia","base_url":"http://eprints.uthm.edu.my/cgi/oai2"},"display":{"title":"Adaptive control for one-DOF finger rehabilitation robot","abstract":"This project presents one of an adaptive control technique to control the DC motor for one-DOF (Degree of Freedom) finger rehabilitation robot. Many different types of controllers are used to provide accurate positioning of the of the DC motor for the rehabilitation robot. One of the common used in controller system is proportional–integral–derivative controller (PID controller). However, the limitation of the PID controller is unable to adapt the variations in the load, as handgrip stiffness can be varied from patient to patient and PID controller is needed to tune for each stiffness. The performance of the robot will be affected and the steady state error occurred when the unknown and inaccessible load torque is imposed. Therefore, in this project, a Model Reference Adaptive Control (MRAC) is proposed to design a stable controller that able to cope with the variations handgrip stiffness to reduce the positioning error and steady state error. The simulated result show that the designed adaptive controller provides good response with reduced settling time and without steady state error for entire range of handgrip stiffness. The MRAC controller will perform better for rehabilitation robot that able to cope with patients without the aid of any additional stiffness detection sensors.","abstract_html":"This project presents one of an adaptive control technique to control the DC motor for one-DOF (Degree of Freedom) finger rehabilitation robot. Many different types of controllers are used to provide accurate positioning of the of the DC motor for the rehabilitation robot. One of the common used in controller system is proportional–integral–derivative controller (PID controller). However, the limitation of the PID controller is unable to adapt the variations in the load, as handgrip stiffness can be varied from patient to patient and PID controller is needed to tune for each stiffness. The performance of the robot will be affected and the steady state error occurred when the unknown and inaccessible load torque is imposed. Therefore, in this project, a Model Reference Adaptive Control (MRAC) is proposed to design a stable controller that able to cope with the variations handgrip stiffness to reduce the positioning error and steady state error. The simulated result show that the designed adaptive controller provides good response with reduced settling time and without steady state error for entire range of handgrip stiffness. The MRAC controller will perform better for rehabilitation robot that able to cope with patients without the aid of any additional stiffness detection sensors.","abstract_has_math":false,"creators":["Jainal Abidin, Nurul Aqilah"],"institution":"Universiti Tun Hussein Onn Malaysia","degree_name":"mphil","degree_level":"masters","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-01","date_published":"2019-01","updated_at":"2026-07-24T05:47:59Z","subjects":["TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. 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One of the common used in controller system is proportional–integral–derivative controller (PID controller). However, the limitation of the PID controller is unable to adapt the variations in the load, as handgrip stiffness can be varied from patient to patient and PID controller is needed to tune for each stiffness. The performance of the robot will be affected and the steady state error occurred when the unknown and inaccessible load torque is imposed. Therefore, in this project, a Model Reference Adaptive Control (MRAC) is proposed to design a stable controller that able to cope with the variations handgrip stiffness to reduce the positioning error and steady state error. The simulated result show that the designed adaptive controller provides good response with reduced settling time and without steady state error for entire range of handgrip stiffness. The MRAC controller will perform better for rehabilitation robot that able to cope with patients without the aid of any additional stiffness detection sensors."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Adaptive control for one-DOF finger rehabilitation robot"]}]}],"canonical_facts":{"dc:creator":["Jainal Abidin, Nurul Aqilah"],"dc:date":["2019-01"],"dc:date.issued":["2019-01"],"dc:description.abstract":["This project presents one of an adaptive control technique to control the DC motor for one-DOF (Degree of Freedom) finger rehabilitation robot. Many different types of controllers are used to provide accurate positioning of the of the DC motor for the rehabilitation robot. One of the common used in controller system is proportional–integral–derivative controller (PID controller). However, the limitation of the PID controller is unable to adapt the variations in the load, as handgrip stiffness can be varied from patient to patient and PID controller is needed to tune for each stiffness. The performance of the robot will be affected and the steady state error occurred when the unknown and inaccessible load torque is imposed. Therefore, in this project, a Model Reference Adaptive Control (MRAC) is proposed to design a stable controller that able to cope with the variations handgrip stiffness to reduce the positioning error and steady state error. The simulated result show that the designed adaptive controller provides good response with reduced settling time and without steady state error for entire range of handgrip stiffness. 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